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Validation of Operational AMSR2 SSTs

Research Topic: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: JPSS PGRR
Published Date: 9/5/2017
AHAH_AMSR_16tn

2017 ANNUAL REPORT

Background

The ability to retrieve SSTs even with 100% cloud cover is an invaluable asset for ocean forecasting and numerical weather prediction, especially during winter months.  For example, the ability to observe rapidly varying SSTs due to strong mixing during the passage of hurricanes is especially useful during the high activity phases of the hurricane season.  The AMSR-2 microwave imaging instrument can retrieve SSTs through clouds, and product is impervious to aerosol contamination.  In addition, AMSR-2 carries a new channel at 7.33 GHz that has the potential to assist in regions of light precipitation and in mitigating the effect of RFI contamination on the retrieval.  It is for these reasons that the timely provision of AMSR-2 SST observations is a highly desirable goal for a number of oceanographic, climate and weather applications.

Accomplishments

The initial, and most important, aspect of the work was to conduct an independent evaluation of the GAASP AMSR-2 SST product prior to operations.  This:

a)      Serves as validation of the end-product, and provides feedback for further adjustment and improvement, as required

b)      We found that comparison against Level-4 analyses is a very powerful tool to identify potential anomalies.

c)       Cross-comparison of errors identified in (d) against other derived parameters (wind speed, precipitation, cloud liquid water and water vapor) aids in discernment of cross-product feedback.

In response to our feedback and suggestions, the GAASP algorithm team developed a 4th version of the product, which has recently been validated and is a substantial improvement (0.62 K rms), with error characteristics that are broadly similar to those observed in other SST products.  Some residual bias dependencies remain and these findings have been passed back to the team.  In addition, a template for the GHRSST L2P product was provided, along with assistance in implementation and debugging.  Most critically, the bias and uncertainty of the SST product has been characterized as a function of observational parameters.  The application of this results in a modest reduction in RMS of ~0.02 K, and is illustrated in Figure 1.  The geographical distribution of this improvement can be discerned from the “before and after” plots of bias versus latitude shown in Figure 2.  The substantial increase in spread at southerly latitudes merits further investigation.

AHAH_AMSR_16A

Planned Work

Below are the planned activities on this project.  Additional progress is anticipated on some of the following tasks, since they are being undertaken/completed this year (i.e. intended by end-June 2016)

  • Refine GHRSST Level-2P Sensor Specific Error Statistics algorithm to account for residual errors in the GAASP AMSR-2 SST product
  • Continue to provide feedback on further revisions to the GAASP AMSR-2 SST product development team

Products

  • Report on GAASP AMSR-2 SST product accuracy;
  • Contribution of materials to NOAA design reviews.

 

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Performance Metrics

# of new or improved products developed that became operational

(please identify below the table)

1

# of products or techniques submitted to NOAA for consideration in operations use

1

# of peer reviewed papers

 

# of NOAA technical reports

 

# of presentations

 

# of graduate students supported by your CICS task

 

# of graduate students formally advised

 

# of undergraduate students mentored during the year

 

 

This task is only part of a major NOAA effort to produce SSTs (and other geophysical products) from AMSR-2 data.  The provision of information (GHRSST L2P template) and development of the necessary SSES estimation algorithm are essential components for the “value-added” GHRSST L2P version of the basic GAASP AMSR-2 SST product.

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